데이터 전처리

+import os
+import numpy as np
+import random
+from imageio import imread
+from skimage.transform import resize
+import hickle as hkl
+from setting import *
+
+#tr : val = 9:1
+desired_im_sz = (128, 160) #높이,너비
+#categories = ['walk', 'run', 'hug', 'crossarms', 'jump', 'clap', 'etc', 'beverage', 'phone', 'calling']
+num_pic = 12 #각 sequence마다 받아올 프레임 개수. (개수가 일정하기 않기 때문)
+
+
+# Create image datasets.
+def process_data():
+    base_dir = os.path.join(DATA_DIR, 'action_data/')
+    temp_list = []
+    source_temp = []  # corresponds to recording that image came from
+    im_list = []
+    source_list = []
+    validation = []
+    val_source = []
+    val_idx =[]
+    num_data = 0 # 비디오 개수
+
+    for top, dir, f in os.walk(base_dir):
+        if(len(f) > 0 and len(f) >= num_pic+1):
+            f.sort()    #오마이갓 이걸 해줘야해,,,,,
+            temp_list += [top+'/'+ f[idx] for idx in range(1,13)]
+            start = top.rfind('/')
+            source_temp += [top[start+1:]] * num_pic
+            num_data += 1
+
+
+    # 파일 2000개만
+    for i in range(1900):
+        t = random.randrange(num_data)
+        im_list += temp_list[t:t+num_pic]
+        source_list += [source_temp[t]] * num_pic
+        del temp_list[t:t+num_pic]
+        del source_temp[t:t+num_pic]
+
+    for i in range(100):
+        t = random.randrange(num_data)
+        validation += temp_list[t:t+num_pic]
+        val_source += [source_temp[t]] * num_pic
+        del temp_list[t:t+num_pic]
+        del source_temp[t:t+num_pic]
+
+    # print(len(im_list), ", ", len(validation))
+
+    X_t = np.zeros((len(im_list),) + desired_im_sz + (3,))
+    X_v = np.zeros((len(validation),) + desired_im_sz + (3,))
+    for i, im_file in enumerate(im_list):
+        im = imread(im_file)
+        X_t[i] = resize(im, (desired_im_sz[0], desired_im_sz[1]))
+
+    for i, im_file in enumerate(validation):
+        im = imread(im_file)
+        X_v[i] = resize(im, (desired_im_sz[0], desired_im_sz[1]))
+            
+    # print(X_t.shape, ", ", X_v.shape)
+    # print(X_t[0], end ='\n\n')
+    # print(X_v[0])
+
+
+    hkl.dump(X_t, os.path.join(DATA_DIR, 'X_train.hkl'))
+    hkl.dump(source_list, os.path.join(DATA_DIR, 'sources_train.hkl'))
+    hkl.dump(X_v, os.path.join(DATA_DIR, 'X_val.hkl'))
+    hkl.dump(val_source, os.path.join(DATA_DIR, 'sources_val.hkl'))
+
+
+if __name__ == '__main__':
+    process_data()
\ No newline at end of file